code: def testQuantizeWrapper_FailsWithModel(self):
      layer = keras.layers.Dense(
          5, activation="relu", input_shape=(10,)
      )
      model = keras.Sequential([layer])
  
      with self.assertRaises(ValueError):
          QuantizeWrapper(
              model,
              quantize_config=self.quantize_registry.get_quantize_config(
                  layer
              ),
          )
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/quantize_wrapper_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_aware_activation
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_wrapper
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantize_registry
label_desc: Use image node_id 6 for calling the QuantizeWrapperTest obj's underlying member method code with example usage: obj.testQuantizeWrapper_FailsWithModel() without return types